摘要
稀释水水力式流浆箱的总压控制直接关系到纸张质量的好坏,传统的PID方法对于非线性、参数时变性和模型不确定性的对象控制精度较低。虽然传统遗传算法可以优化PID参数,提高精度,但是收敛速度慢,整定时间长,限制其在高速纸机控制中的应用。针对这些问题,本课题以纸机流浆箱总压控制为研究对象,采用改进的遗传算法来整定PID参数,通过优化交叉和变异算子、增加当前最优追踪策略以及改进收敛准则等方法来提高遗传算法的全局寻优能力和收敛速度。仿真结果表明,用改进的遗传算法整定后的流浆箱总压控制PID具有更快的响应速度和更好的鲁棒性。
The total pressure control of the diluted water hydraulic headbox is directly related to the quality of the paper. The traditional PID method has low control precision for the object which is nonlinear, parameter time-varying and model uncertainty. Although the traditional ge- netic algorithm can optimize the PID parameters and improve the precision, it has a slow convergence speed and a long dynamic response time, which limit its application in the control of high speed paper machine. Aiming at these problems, an improved genetic algorithm, which optimize the operators of crossover and mutation, take the optimal tracking strategy and inprove convergence criterion to enhance theorenall optimization ability of genetic algorithm and speed up the convergence rate, was employed in this paper to tune the PID parameters in total pressure control of headbox of the paper-making machine. The simulation results showed that the proposed method had faster response speed and better robustness than the Z-N tuning and traditional genetic algorithm.
作者
莫卫林
杨浩
熊智新
胡慕伊
MO Wei-lin YANG Hao XIONG Zhi-xin HU Mu-yi(Jiangsu Provincial Key Lab of Pulp and Paper Science and Technology, Nanjing Forestry University, Nanfing , Jiangsu Province, 210037)
出处
《中国造纸》
CAS
北大核心
2017年第8期35-40,共6页
China Pulp & Paper
基金
国家林业局948项目"农林剩余物制机械浆节能和减量技术引进"(2014-4-3)
关键词
流浆箱总压
PID参数优化
改进遗传算法
total pressure of headbox
PID parameter optimization
improved genetic algorithm
